# Knowledge Base Completion using Web-Based Question Answering and Multimodal Fusion

arXiv: https://arxiv.org/abs/2211.07098 · HTML: https://mlsanity.com/paper/2211.07098/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 14 references that are in the map.
- First posted on arXiv 14 Nov 2022.

## Built on by (most cited first, 2 of 2)

- [Query-Driven Knowledge Base Completion using Multimodal Path Fusion over Multimodal Knowledge Graph](https://mlsanity.com/paper/2212.01923/) (2022)
- [Finding Lookalike Customers for E-Commerce Marketing](https://mlsanity.com/paper/2301.03147/) (2023)

## Abstract (arXiv)

Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge. However, these knowledge bases are highly incomplete. To solve this problem, we propose a web-based question answering system system with multimodal fusion of unstructured and structured information, to fill in missing information for knowledge bases. To utilize unstructured information from the Web for knowledge base completion, we design a web-based question answering system using multimodal features and question templates to extract missing facts, which can achieve good performance with very few questions. To help improve extraction quality, the question answering system employs structured information from knowledge bases, such as entity types and entity-to-entity relatedness.